AI Compute & Silicon · nvidia.com
NVIDIA
141 verified customer use cases (96% with quantified ROI · Avg Value Score 93.3 · 100% with mapped architecture components).
- Verified stories
- 141
- Quantified ROI
- 96%
- Avg value score
- 93.3
- Industries served
- 17
- Distinct products
- 428
NVIDIA Sample Feb 2, 2026 Lowe’s Lowe’s needed to close product-expertise gaps for project-based shoppers and store associates, gain better visibility inside large stores, and modernize slow, expensive merchandising and planogram processes across its… 1,750+ stores with digital twins updated throughout the day Dell PowerEdge XR Series servers · Hyper3D.ai’s Rodin · Mylow NVIDIA Sample Feb 2, 2026 Agility Robotics Agility Robotics needed a reliable way to train whole-body control for humanoid robots that could work in human-built warehouses and factories without costly facility redesigns or risky trial-and-error learning on the… billions of simulation steps Isaac Lab · MuJoCo · NVIDIA GPUs NVIDIA Sample Feb 2, 2026 Parabole AI Parabole AI needed to make causal industrial optimization practical at scale, but CPU-based causal analysis and brute-force optimization made complex production and energy-planning scenarios too slow to support… 1,000x speedup Gurobi Optimization Solver · NVIDIA GH200 Grace Hopper Superchip · Parabole TRAIN NVIDIA Sample Feb 2, 2026 FastLabel FastLabel needed to prepare large computer-vision datasets for autonomous-driving and industrial workloads, but manual captioning and duplicate review made image curation slow, expensive, and too error-prone to keep up… $0.26 on an A100 GPU Google Cloud Platform · NVIDIA A100 · NVIDIA NeMo Curator NVIDIA Sample Feb 2, 2026 FanDuel TV and Verizon FanDuel TV and Verizon needed a portable production architecture that could move high-volume live sports feeds with lower latency and stronger security than cloud backhaul while still supporting AI-assisted camera… More than 130 racetracks nationwide NVIDIA AI Enterprise · NVIDIA Holoscan for Media · NVIDIA L40S GPUs NVIDIA Sample Feb 2, 2026 Baseten Baseten needed to orchestrate a global, multi-cloud GPU fleet for increasingly large reasoning models while improving latency, throughput, and cost efficiency enough to keep real-time AI inference practical for… 25% better cost performance for latency-sensitive inference Baseten Inference Stack · Google Cloud A4 VMs · NVIDIA Blackwell NVIDIA Sample Feb 2, 2026 Sight Machine Manufacturers needed a faster way to understand equipment issues, share floor knowledge across shifts, and resolve downtime without forcing operators to piece together disconnected plant data and static reports. Up to 10% improvement in line productivity NVIDIA A10 GPUs on Azure · NVIDIA Omniverse · Omniverse Kit App Streaming NVIDIA Sample Feb 2, 2026 Amway Amway wanted to scale internal and marketer-facing generative AI while keeping data secure, inference efficient, and operations manageable, but it needed a controlled infrastructure for document analysis, presentation… 35 days to 15 days NVIDIA AI Enterprise · NVIDIA Base Command Manager Essentials · NVIDIA DeepSeek R1 NIM NVIDIA Sample Feb 2, 2026 Worley Worley needed to unlock more than 50 years of engineering knowledge across over 100,000 documents, but fragmented tools, isolated repositories, and slow document retrieval caused engineers to waste time and made it hard… 100,000+ documents Microsoft Azure · Milvus · NVIDIA AI Enterprise NVIDIA Sample Feb 2, 2026 Foxconn Foxconn needed to reduce nurse burnout and repetitive transport work in hospitals, but deploying autonomous clinical robots required safe simulation, real-time edge perception, and dependable navigation inside busy… 2-3 hours a day NVIDIA Isaac Sim · NVIDIA Isaac for Healthcare · NVIDIA Jetson AGX Orin NVIDIA Sample Feb 2, 2026 MIT and Recursion MIT and Recursion needed an open model that could co-fold protein complexes and predict binding affinity with the speed of foundation-model inference instead of the cost and delay of physics-based simulation, but… 63 DGX H100 systems NVIDIA BioNeMo NIM microservice · NVIDIA DGX SuperPOD with DGX H100 · NVIDIA Quantum-2 InfiniBand networking NVIDIA Sample Jan 30, 2026 Harvard Medical School The Walter Lab at Harvard Medical School needed to map protein-protein interactions at proteome scale to study DNA repair and disease mechanisms, but manual structural biology work and false-positive model predictions… 1.7 million protein interaction predictions in three months ColabFold · KIRC · NVIDIA A100 GPUs NVIDIA Sample Archived · Jan 28, 2026 City of Raleigh Raleigh needed to improve congestion management, mobility, and street safety as the city grew, but manual traffic counts and disconnected sensor repositories made it hard to visualize conditions, respond to incidents… $9.7 million annually in time and fuel costs Esri ArcGIS · Microsoft Azure · NVIDIA Blueprint for video search and summarization (VSS) NVIDIA Sample Jan 27, 2026 Argonne National Laboratory Argonne and its collaborators needed to coordinate gravitational-wave and radio follow-up across observatories without moving proprietary datasets, but CPU-bound processing, siloed data-sharing policies, and slow… 5-10x speedup compared to CPU workloads Dingo-BNS · NVIDIA A100 Tensor Core GPUs · NVIDIA A40 GPUs NVIDIA Sample Jan 23, 2026 Government of Cantabria Cantabria's small six-person GIS team needed to produce more environmental and infrastructure mapping output with limited staff, but manual cartography and legacy stereo-mapping workflows were too slow and too expensive… 1:5,000-scale mapping completed in just three days Esri ArcGIS Pro · GeoAI · MaskRCNN NVIDIA Sample Jan 12, 2026 XPAI XPAI needed a privacy-preserving way to measure how people use and perceive physical spaces so brands and event operators could optimize offline experiences with real-time evidence instead of intuition. millions of data points per second AVAI One Sensor · NVIDIA DeepStream SDK · NVIDIA Jetson Orin NVIDIA Sample Jan 7, 2026 Delta Electronics Delta Electronics needed to reconfigure complex production lines and train inspection models quickly, but manual position-switch changes, fragmented 3D tools, and slow hand-labeled image collection were driving downtime… 10 minutes NVIDIA Isaac Sim · NVIDIA Omniverse Libraries · NVIDIA Omniverse Replicator NVIDIA Sample Jan 6, 2026 TGen TGen needed to analyze rapidly growing single-cell and spatial multi-omics datasets, but standard tertiary analysis workflows took 10-14 hours per run and became prohibitive when researchers needed to iterate across… 10 hours to 10 minutes on the first RAPIDS run 10x Genomics Xenium Analyzer · NVIDIA RAPIDS · Scanpy NVIDIA Sample Dec 4, 2025 Hippocratic AI Hippocratic AI needed to scale safe, empathetic patient outreach and follow-up without adding clinician workload, but real-time voice inference, safety review, and HIPAA-sensitive operations created demanding latency… 100,000 patients in one day Amazon SageMaker HyperPod · NVIDIA H200 Tensor Core GPUs · Polaris constellation architecture NVIDIA Sample Oct 29, 2025 Lockheed Martin Lockheed Martin needed a secure, centralized AI platform that could replace fragmented compute, tooling, and workflows, keep sensitive and classified data on premises, and let thousands of engineers build trustworthy AI… 122,000 employees globally CUDA · Lockheed Martin AI Factory · Lockheed Martin Text Navigator NVIDIA Sample Oct 29, 2025 Insider Insider needed a faster and more cost-effective way to localize video content for non-English-speaking audiences because traditional dubbing was too slow and expensive and subtitles delivered lower engagement. 100 million views NVIDIA A100 GPUs · NVIDIA TensorRT · NVIDIA Triton Inference Server NVIDIA Sample Oct 24, 2025 Universal Robots Universal Robots needed to move collaborative robots beyond static programmed tasks so manufacturers in dynamic, high-mix environments could deploy cobots for adaptive assembly and machine-tending work without complex… Accurate 3D pose estimation with minimal training AI Accelerator · NVIDIA Isaac · NVIDIA Isaac Lab NVIDIA Sample Sep 1, 2025 Innophore Innophore needed to predict protein-ligand interactions and off-target effects much earlier in drug discovery, but the scale of biomolecular computation made traditional CPU workflows too slow and too expensive for… 15 million new variants of SARS-CoV-2 AWS · AlphaFold · ESMfold NVIDIA Sample Aug 29, 2025 Siemens Healthineers Siemens Healthineers needed to speed up radiation-oncology model development and reduce the time clinicians spend contouring organs at risk so treatment planning could scale with rising cancer demand. 100 Gbps Mellanox InfiniBand network Mellanox InfiniBand · NVIDIA HGX-1 · NVIDIA HGX-2